Inooka Taiga, Kominami Taro, Tomita Ryo, Suzumura Ayana, Matsuno Tsuyoshi, Ota Junya, Koyanagi Yoshito, Takeyama Hideo, Ueno Shinji, Ito Yasuki, Nishiguchi Koji M, Yuki Kenya
Department of Ophthalmology, Nagoya University Graduate School of Medicine, 65 Tsuruma-cho, Showa-ku, Nagoya, 466- 8550, Japan.
Department of Internal Medicine, Aichi Health Promotion Foundation, Nagoya, Japan.
Sci Rep. 2024 Dec 5;14(1):30342. doi: 10.1038/s41598-024-82096-1.
Measurement of anterior chamber depth (ACD), an important marker for the screening of primary angle-closure glaucoma, requires biometry, which is not readily used. This study assessed the relationship between ACD and health check-up data findings from participants with good corrected visual acuity in Japan. Participants underwent ophthalmic, anthropometric, and hematological assessments. The mean ACD of all 3060 participants was 3.33 ± 0.34 mm [2.22-4.72 mm]. Multivariable linear regression analysis was performed to determine factors that were significantly correlated with ACD, and logistic regression analysis was performed to predict ACD < 2.70 mm. Multivariable linear regression analysis showed that age, sex, intraocular pressure, spherical equivalent refractive error (SER), height, and fasting blood sugar levels significantly correlated with ACD (P < 0.05). Logistic regression analysis showed that age, sex, and SER were the best predictors of ACD < 2.70 mm. The area under receiving operator characteristic curves of 'age and SER' and 'age, SER, and sex' were 0.821 and 0.835, respectively, with no significant difference (P = 0.122). In conclusion, ACD correlates with several parameters, and age and SER may be particularly important for predicting ACD in participants undergoing health checkups.
前房深度(ACD)的测量是原发性闭角型青光眼筛查的一项重要指标,需要进行生物测量,而生物测量并不容易实施。本研究评估了日本视力矫正良好的参与者的ACD与健康检查数据结果之间的关系。参与者接受了眼科、人体测量学和血液学评估。3060名参与者的平均ACD为3.33±0.34毫米[2.22 - 4.72毫米]。进行多变量线性回归分析以确定与ACD显著相关的因素,并进行逻辑回归分析以预测ACD < 2.70毫米。多变量线性回归分析表明,年龄、性别、眼压、等效球镜度(SER)、身高和空腹血糖水平与ACD显著相关(P < 0.05)。逻辑回归分析表明,年龄、性别和SER是ACD < 2.70毫米的最佳预测因素。“年龄和SER”以及“年龄、SER和性别”的受试者工作特征曲线下面积分别为0.821和0.835,无显著差异(P = 0.122)。总之,ACD与多个参数相关,年龄和SER对于预测健康检查参与者的ACD可能尤为重要。